Sequence clustering strategies improve remote homology recognitions while reducing search times

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چکیده

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Sequence clustering strategies improve remote homology recognitions while reducing search times.

Sequence databases are rapidly growing, thereby increasing the coverage of protein sequence space, but this coverage is uneven because most sequencing efforts have concentrated on a small number of organisms. The resulting granularity of sequence space creates many problems for profile-based sequence comparison programs. In this paper, we suggest several strategies that address these problems, ...

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Improved performance of sequence search algorithms in remote homology detection

The protein sequence space is vast and diverse, spanning across different families. Biologically meaningful relationships exist between proteins at superfamily level. However, it is highly challenging to establish convincing relationships at the superfamily level by means of simple sequence searches. It is necessary to design a rigorous sequence search strategy to establish remote homology rela...

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Faster sequence homology searches by clustering subsequences

MOTIVATION Sequence homology searches are used in various fields. New sequencing technologies produce huge amounts of sequence data, which continuously increase the size of sequence databases. As a result, homology searches require large amounts of computational time, especially for metagenomic analysis. RESULTS We developed a fast homology search method based on database subsequence clusteri...

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Remote Homology Detection Using Local Sequence-Structure Correlations

Remote homology detection refers to the problem of detecting protein homology in cases of low sequence similarity. Existing methods to establish homology relationships via sequence similarity do not work well for these remote homology. In this paper, we present a new method, SVM-HMMSTR, that overcomes the reliance on sequence similarity by taking into consideration the local structure similarit...

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CPHmodels-3.0—remote homology modeling using structure-guided sequence profiles

CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly...

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ژورنال

عنوان ژورنال: Protein Engineering, Design and Selection

سال: 2002

ISSN: 1741-0134,1741-0126

DOI: 10.1093/protein/15.8.643